SURF (stroke with underlying risk of atrial fibrillation): Proposals for a definition

Suissa, Laurent; Bertora, David; Kalle, Roger; Bruno, Chiara; Romero, Gustavo Adolfo Sierra; Mahagne, Marie-Hélène

doi:10.1016/j.clineuro.2019.04.028

Cited by 5 publications

(9 citation statements)

References 41 publications

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“…18 Over the last decade, several scoring systems have been proposed to predict paroxysmal covert AF using clinical data, ECG, Holter ECG, cardiac echography, laboratory, and brain imaging. [4][5][6]18 To characterize the population of the cohort, several of these scoring systems were tested. All the main classical predictors of cardioembolic stroke such as age, the clinical severity assessed by NIHSS at admission, and plasma levels of BNP [4][5][6]18 applied significantly to patients with stroke of cardiac origin.…”

Section: Discussionmentioning

confidence: 99%

“…[4][5][6]18 To characterize the population of the cohort, several of these scoring systems were tested. All the main classical predictors of cardioembolic stroke such as age, the clinical severity assessed by NIHSS at admission, and plasma levels of BNP [4][5][6]18 applied significantly to patients with stroke of cardiac origin. Plasmatic BNP is considered to be an integrative variable, 19 and it was found to be an independent predictor of cardioembolic stroke among all previous variables in the multivariate analysis.…”

Section: Discussionmentioning

confidence: 99%

“…The age and stroke severity NIHSS >5 to identify AF 5 was calculated from the sum of the following variables: age (0.76 points/y), stroke severity NIHSS ≤5 (9 points) and NIHSS >5 (21 points). Finally, the score for stroke with an underlying risk of AF (SURF) 6 was calculated by adding the age (year) multiplied by 10 to the plasmatic level of BNP (pg/mL). Among these 3 previous composite scores, only SURF was significantly associated with cardioembolic stroke.…”

Section: Classical Predictors Of Cardioembolic Strokementioning

confidence: 99%

“…2,3 In half of these cases, AF is not identified, and its diagnosis remains a challenge for the clinician. [4][5][6] Indeed, only 5% of new AF diagnoses are documented by a 24-hour Holter electrocardiogram (ECG) performed in clinical practice for patients with AF-naive stroke. 7 Prolonged Holter ECG or an implantable ECG recorder improve the covert paroxysmal AF diagnostic rate 7 but these diagnostic tools are not used in clinical routine for reasons of cost and accessibility, particularly in elderly patients with stroke.…”

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confidence: 99%

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Combined Omic Analyzes of Cerebral Thrombi: A New Molecular Approach to Identify Cardioembolic Stroke Origin

Suissa

Guigonis

Graslin

et al. 2021

Stroke

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Background and Purpose: The diagnosis of cardioembolic stroke can be challenging for patient management in secondary stroke prevention, particularly in the case of covert paroxysmal atrial fibrillation. The molecular composition of a cerebral thrombus is related to its origin. Therefore, proteomic and metabolomic analyses of the retrieved thrombotic material should allow the identification of biomarkers or signatures to improve the etiological diagnosis of stroke. Methods: In this pilot study, the proteome and metabolome of cerebral thrombi from atherothrombotic and cardioembolic stroke patients were studied according to ASCOD phenotyping (A: atherosclerosis; S: small-vessel disease; C: cardiac pathology; O: other causes; D: dissection), with the highest causality grade, from the ThrombiOMIC cohort (consecutive patients with stroke recanalized by mechanical thrombectomy in an acute phase). Proteomic and metabolomic results were used separately or combined, and the obtained omic signatures were compared with classical cardioembolic stroke predictors using pairwise comparisons of the area under receiver operating characteristics. Results: Among 59 patients of the ThrombiOMIC cohort, 34 patients with stroke showed a cardioembolic phenotype and 7 had an atherothrombotic phenotype. Two thousand four hundred fifty-six proteins and 5019 molecular features of the cerebral thrombi were identified using untargeted proteomic and metabolomic approaches, respectively. Area under receiver operating characteristics to predict the cardioembolic origin of stroke were calculated using the proteomic results (0.945 [95% CI, 0.871–1]), the metabolomic results (0.836 [95% CI, 0.714–0.958]), and combined signatures (0.996 [95% CI, 0.984–1]). The diagnostic performance of the combined signatures was significantly higher than that of classical predictors such as the plasmatic BNP (B-type natriuretic peptide) level (area under receiver operating characteristics, 0.803 [95% CI, 0.629–0.976]). Conclusions: The combined proteomic and metabolomic analyses of retrieved cerebral thrombi is a very promising molecular approach to predict the cardioembolic cause of stroke and to improve secondary stroke prevention strategies.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Classical Predictors Of Cardioembolic Strokementioning

confidence: 99%

mentioning

confidence: 99%

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Combined Omic Analyzes of Cerebral Thrombi: A New Molecular Approach to Identify Cardioembolic Stroke Origin

Suissa

Guigonis

Graslin

et al. 2021

Stroke

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“…Recently, Suissa et al used proteomic and metabolomic approaches in retrieved thrombi from AIS patients sampled consecutively to predict a CE vs. LAA etiology according to the ASCOD classification (A: atherosclerosis; S: small-vessel disease; C: cardiac pathology; O: other causes; D: dissection) [ 59 ]. Using liquid chromatography and mass spectrometry, the authors quantified a specific proteomic and metabolomic molecular signature in both groups and built a model with a significantly better predictive power (100% sensitivity/85.7% specificity) than classic clinical predictors of CE stroke (age, clinical severity at admission, and plasma levels of brain natriuretic peptide) [ 60 , 61 ]. In addition, they distinguished a peculiar proteomic signature in the 2 groups, with increased glycophorin-A (marker of red blood cells) and fibrinogen in CE strokes.…”

Section: Multiomic Studiesmentioning

confidence: 99%

Advancing Stroke Research on Cerebral Thrombi with Omic Technologies

Costamagna

Bonato

Corti

et al. 2023

IJMS

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Cerebrovascular diseases represent a leading cause of disability, morbidity, and death worldwide. In the last decade, the advances in endovascular procedures have not only improved acute ischemic stroke care but also conceded a thorough analysis of patients’ thrombi. Although early anatomopathological and immunohistochemical analyses have provided valuable insights into thrombus composition and its correlation with radiological features, response to reperfusion therapies, and stroke etiology, these results have been inconclusive so far. Recent studies applied single- or multi-omic approaches—such as proteomics, metabolomics, transcriptomics, or a combination of these—to investigate clot composition and stroke mechanisms, showing high predictive power. Particularly, one pilot studies showed that combined deep phenotyping of stroke thrombi may be superior to classic clinical predictors in defining stroke mechanisms. Small sample sizes, varying methodologies, and lack of adjustments for potential confounders still represent roadblocks to generalizing these findings. However, these techniques hold the potential to better investigate stroke-related thrombogenesis and select secondary prevention strategies, and to prompt the discovery of novel biomarkers and therapeutic targets. In this review, we summarize the most recent findings, overview current strengths and limitations, and present future perspectives in the field.

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Prediction of underlying atrial fibrillation in patients with a cryptogenic stroke: results from the NOR-FIB Study

Ratajczak-Tretel¹,

Lambert²,

Al-Ani³

et al. 2023

J Neurol

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Background Atrial fibrillation (AF) detection and treatment are key elements to reduce recurrence risk in cryptogenic stroke (CS) with underlying arrhythmia. The purpose of the present study was to assess the predictors of AF in CS and the utility of existing AF-predicting scores in The Nordic Atrial Fibrillation and Stroke (NOR-FIB) Study. Method The NOR-FIB study was an international prospective observational multicenter study designed to detect and quantify AF in CS and cryptogenic transient ischaemic attack (TIA) patients monitored by the insertable cardiac monitor (ICM), and to identify AF-predicting biomarkers. The utility of the following AF-predicting scores was tested: AS5F, Brown ESUS-AF, CHA2DS2-VASc, CHASE-LESS, HATCH, HAVOC, STAF and SURF. Results In univariate analyses increasing age, hypertension, left ventricle hypertrophy, dyslipidaemia, antiarrhythmic drugs usage, valvular heart disease, and neuroimaging findings of stroke due to intracranial vessel occlusions and previous ischemic lesions were associated with a higher likelihood of detected AF. In multivariate analysis, age was the only independent predictor of AF. All the AF-predicting scores showed significantly higher score levels for AF than non-AF patients. The STAF and the SURF scores provided the highest sensitivity and negative predictive values, while the AS5F and SURF reached an area under the receiver operating curve (AUC) > 0.7. Conclusion Clinical risk scores may guide a personalized evaluation approach in CS patients. Increasing awareness of the usage of available AF-predicting scores may optimize the arrhythmia detection pathway in stroke units.

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SURF (stroke with underlying risk of atrial fibrillation): Proposals for a definition

Cited by 5 publications

References 41 publications

Combined Omic Analyzes of Cerebral Thrombi: A New Molecular Approach to Identify Cardioembolic Stroke Origin

Combined Omic Analyzes of Cerebral Thrombi: A New Molecular Approach to Identify Cardioembolic Stroke Origin

Advancing Stroke Research on Cerebral Thrombi with Omic Technologies

Prediction of underlying atrial fibrillation in patients with a cryptogenic stroke: results from the NOR-FIB Study

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